Feature point reduction for blood vessel biometric system

ABSTRACT

To suitably reduce data amount. For example, feature points from a branch point or an end point to the next branch point or an end point in a blood vessel line are set as a group. In the three feature points satisfying one of the condition that the absolute value of the outer product of vectors in continuous three feature points is smaller than an outer product threshold value, and the condition that a cosine in the above three feature points is smaller than a cosine threshold value, the middle one of the three feature points satisfying the other of the above conditions and being the smallest is eliminated, for every group.

CROSS REFERENCE TO RELATED APPLICATION

The present invention contains subject matter related to Japanese PatentApplications JP 2007-046089 filed in the Japanese Patent Office on Feb.26, 2007 and JP 2006-207033 filed on Jul. 28, 2006, the entire contentsof which being incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an image processing method, an imageprocessing apparatus and a program therefor, and is applicable to a caseof performing biometrics authentication, for example.

2. Description of the Related Art

Heretofore, as an object of biometrics authentication, there is a bloodvessel. Generally, an authentication apparatus registers the image ofblood vessels obtained by imaging in a memory as information to identifythe living body that was imaged at the time, or determines whether ornot the imaged person is the said registered person by comparing withthe above registered image of blood vessels.

By the way, in recent years, reducing data amount when in registeringdata in a memory or the like has been desired. As a countermeasure tothis, there has been a technique to register only a feature point(position) in blood vessels in the above image, without registering theimage of the blood vessels (Japanese Patent Laid-Open No. 1998-295674,for example). As a concrete technique to extract a feature point from ablood vessel, there is a technique called Harris Corner, for example.

SUMMARY OF THE INVENTION

However, in the above technique, also a point at a gentle curve part ina blood vessel is extracted as a corner. Therefore, a point not becominga feature component is often extracted, and it also often becomesinsufficient in the amount of data reduction. More particularly, thisproblem clearly exists as the image quality of a camera for imaging ablood vessel becomes higher.

On the other hand, in the blood vessel in the same image, if too manypoints are eliminated, a meaning as identification information may belost. Therefore, a technique which can properly extract a point as afeature component of a blood vessel without losing a meaning asidentification information is desired.

In view of the foregoing, it is desirable to provide an image processingmethod, an image processing apparatus and a program therefor in thatinformation amount can be suitably reduced.

According to an embodiment of the present invention, there is providedan image processing method, an image processing apparatus and a programtherefor that eliminate a feature point being a feature as a componentof an outline, in the outlines of an object included in the image ofinputted image data, and in a branch point, en end point, and a curvepoint detected as the feature point of the outline, feature points froma branch point or an end point to the next branch point or an end pointare assigned as a group. By assigning the feature points from a branchpoint or an end point to the next branch point or an end point as agroup as the above, processing of the outline can be performed in asegment unit without branching. Then, the middle one of the threefeature points satisfying the condition that the product of vectors inthe continuous three feature points is smaller than a predeterminedthreshold value and being the smallest is eliminated, for every saidgroup.

Because the size of the area of a parallelogram formed by continuousthree feature points is simply added in consideration, the middle of thefeature points in that the linearity of the segment connecting the threefeature points is high can be accurately selected as an eliminationobject. Thereby, the feature point can be eliminated so that the outlineafter elimination becomes simple (smooth), as well as approximating theforms of the outline before elimination and the outline afterelimination.

In addition to this, since a feature point at the part that most havethe linearity in the feature points in a group is set as a soleelimination object, a feature point being an elimination object can beselected from a general viewpoint not locally, in comparison with thecase of adopting the processing that watches the above two conditions atthe same time, and eliminates a corresponding feature point every timewhen the above condition is satisfied. Thus, a feature point can befurther accurately eliminated.

Furthermore, the two feature points satisfying the condition that asegment connecting continuous two feature points is smaller than apredetermined segment threshold value is replaced to either an innerdividing point that internally divides the segment at the rate of afirst area that is formed by the above two feature points and a featurepoint connected to one of the two feature points, to a second area thatis formed by the above two feature points and a feature point connectedto the other of the two feature points, or the intersection of aprolongation line that connects one of the above two feature points anda feature point connected to this, and a prolongation line that connectsthe other of the above two feature points and a feature point connectedto this, for every group. By generating a new feature point with addingin consideration the position of a feature point connected to the twofeature points without only simply aiming at two feature points forminga short segment, a feature point can be eliminated so that the outlineof an object after elimination becomes simple (smooth), as well asapproximating the forms of the outline before elimination and theoutline after elimination.

According to an embodiment of the present invention, an image processingmethod, an image processing apparatus and a program therefor in thatinformation amount can be suitably reduced by eliminating a featurepoint so that the outline of an object becomes simple (smooth) as wellas approximating the forms of the outline before elimination and theoutline after elimination can be realized.

The nature, principle and utility of the present invention will becomemore apparent from the following detailed description when read inconjunction with the accompanying drawings in which like parts aredesignated by like reference numerals or characters.

BRIEF DESCRIPTION OF THE DRAWINGS

In the accompanying drawings:

FIG. 1 is a block diagram showing the overall configuration of anauthentication apparatus according to this embodiment;

FIG. 2 is a block diagram showing the functional configuration of firstfeature point extraction processing;

FIGS. 3A to 3C are schematic diagrams showing the appearance patterns ofblack pixels in the neighborhood of an end point, a branch point and anisolated point;

FIGS. 4A to 4C are schematic diagrams for explaining the direction of anend point, a branch point and an isolated point;

FIG. 5 is a schematic diagram for explaining the detection of a curvepoint based on an end point and a branch point;

FIG. 6 is a schematic diagram for explaining the tracking rough line ofa black pixel;

FIGS. 7A and 7B are schematic diagrams showing the appearance patternsof black pixels in the neighborhood of a point on a straight line and acurve point;

FIG. 8 is a schematic diagram for explaining the detection of a curvepoint;

FIGS. 9A to 9C are schematic diagrams showing the search order patternsof a pixel in tracking;

FIG. 10 is a schematic diagram for explaining the search of a blackpixel;

FIG. 11 is a schematic diagram for explaining the processing unit ofcurve point elimination;

FIG. 12 is a schematic diagram for explaining the elimination of a curvepoint in the neighborhood of a branch point;

FIG. 13 is a schematic diagram for explaining a curve point beforeelimination and after elimination;

FIGS. 14A and 14B are schematic diagrams for explaining an effect on ablood vessel line by the elimination of a curve point;

FIG. 15 is a flowchart showing the elimination processing procedure of acurve point on a second stage;

FIG. 16 is a schematic diagram for explaining the elimination of a curvepoint based on an outer product and a cosine;

FIGS. 17A and 17B are schematic diagrams for explaining the replacementof a curve point;

FIG. 18 is a flowchart showing the elimination processing procedure of acurve point on a third stage;

FIG. 19 is a schematic diagram for explaining the elimination of a curvepoint in a Z-form blood vessel line;

FIG. 20 is a schematic diagram for explaining the elimination of a curvepoint in a U-form blood vessel line;

FIG. 21 is a flowchart showing the elimination processing procedure of acurve point on a fourth stage;

FIG. 22 is a schematic diagram for explaining the elimination of a curvepoint based on an outer product;

FIG. 23 is a schematic diagram for explaining the elimination of an endpoint;

FIG. 24 is a schematic diagram for explaining a connection (threebranches) of partial blood vessel lines;

FIG. 25 is a schematic diagram for explaining a connection (fourbranches) of partial blood vessel lines;

FIG. 26 is a schematic diagram showing the relationship between thepixels of an original blood vessel line and the pixels of a blood vesselline to be restored;

FIG. 27 is a schematic diagram for explaining the search of a firstchange position that is most approximate to an original blood vesselline;

FIG. 28 is a schematic diagram showing the result of a first change;

FIG. 29 is a schematic diagram for explaining the search of a secondchange position that is most approximate to an original blood vesselline;

FIG. 30 is a schematic diagram showing the result of a second change;

FIGS. 31A to 31C are schematic diagrams showing blood vessel imagesbefore and after feature point extraction processing (1);

FIG. 32 is a block diagram showing the functional configuration ofsecond feature point extraction processing;

FIG. 33 is a schematic diagram for explaining the determination of thepassing rate of a segment to an original blood vessel line pixel;

FIGS. 34A to 34D are flowcharts showing an elimination processingprocedure;

FIG. 35 is a schematic diagram showing a curve point before eliminationand after elimination;

FIGS. 36A to 36C are schematic diagrams showing blood vessel imagesbefore and after feature point extraction processing (2);

FIG. 37 is a schematic diagram for explaining a search area on the threedimensions centering a remarked pixel;

FIGS. 38A to 38C are schematic diagrams for explaining the detection ofan end point, a branch point, an isolated point in a three-dimensionalblood vessel line;

FIG. 39 is a schematic diagram for explaining the tracking of athree-dimensional blood vessel line; and

FIGS. 40A and 40B are schematic diagrams for explaining the switching ofa division pattern in a search area.

DETAILED DESCRIPTION OF THE EMBODIMENT

Preferred embodiments of the present invention will be described withreference to the accompanying drawings:

(1) Overall Configuration of Authentication Apparatus According to thisEmbodiment

FIG. 1 shows the overall configuration of an authentication apparatusaccording to this embodiment. The authentication apparatus 1 is formedby that an operating part 11, a blood vessel imaging part 12, a flashmemory 13, an interface for transmitting/receiving data to/from anexternal apparatus (hereinafter, this is referred to as an externalinterface) 14 and a notification part 15 are connected to a control part10 respectively via a bus 16.

The control part 10 is a microcomputer including a central processingunit (CPU) for controlling the whole authentication apparatus 1, a readonly memory (ROM) in that various programs and set information arestored, and a random access memory (RAM) serving as a work memory forthe above CPU.

To the control part 10, an execution command COM1 in a mode to registerthe blood vessels of a user to be registered (hereinafter, this isreferred to as a registering person) (hereinafter, this is referred toas a blood vessel registration mode) or an execution command COM2 in amode to determine the presence of the said registering person(hereinafter, this is referred to as an authentication mode) is suppliedfrom the operating part 11, according to the user's operation.

The control part 10 determines a mode to be executed based on the aboveexecution commands COM1, COM2. Based on a program corresponding to thisdetermination result, the control part 10 properly controls the bloodvessel imaging part 12, the flash memory 13, the external interface 14and the notification part 15, to execute the blood vessel registrationmode or the authentication mode.

(1-1) Blood Vessel Registration Mode

In the case where the control part 10 determined the blood vesselregistration mode as a mode to be executed, the control part 10 shiftsan operating mode to the blood vessel registration mode, and controlsthe blood vessel imaging part 12.

In this case, a drive control part 12 a in the blood vessel imaging part12 performs the drive control of one or more near infrared light sourcesLS for emitting near infrared lights to a predetermined position in theauthentication apparatus 1, and an image pickup device ID for examplebeing a charge coupled device (CCD) in an imaging camera CM.

When a finger is disposed at a predetermined, near infrared lightsemitted from the near infrared light source LS passes through the insideof the finger as reflected and dispersed, and is emitted to the imagepickup device ID via an optical system OP, as lights projecting theblood vessels of the finger (hereinafter, this is referred to as a bloodvessel projecting light). The image pickup device ID performsoptical/electrical conversion to the blood vessel projecting lights, andtransmits the result of the above optical/electrical conversion to thedrive control part 12 a as an image signal S1.

In this connection, practically, some of the near infrared lightsemitted to the finger are reflected on the surface of the above fingerand then are emitted to the image pickup device ID. Therefore, the imageof the image signal S1 outputted from the image pickup device ID becomesthe state that the outline of the finger and the fingerprint are alsoincluded, in addition to the blood vessels inside the finger.

The drive control part 12 a adjusts the lens position of an optical lensin the optical system OP so as to focus on the blood vessels inside thefinger, based on the pixel value of this picture, and also adjusts anexposure time to the image pickup device ID so that an amount ofincident light to be entered into the image pickup device ID becomes anadaptive amount. After the above adjustment, the drive control part 12 asupplies an image signal S2 outputted from the image pickup device ID tothe control part 10.

The control part 10 sequentially performs edge processing, smoothingprocessing, binary processing and line thinning processing to the imagesignal S2, to extract the blood vessels included in a picture in theabove image signal S2. Then, in the blood vessel, the control part 10executes the processing for extracting a point being a feature as acomponent of the above blood vessel (hereinafter, this is referred to asa feature point) (hereinafter, this is referred to as feature pointextraction processing). Thus obtained information showing a plurality offeature points (hereinafter, this is referred to as positioninformation) and information showing the connection relationship ofthese feature points (hereinafter, this is referred to as phaseinformation) is stored in the flash memory 13 as registration data D1.

In this manner, the control part 10 can execute the blood vesselregistration mode.

(1-2) Authentication Mode

On the other hand, in the case where the control part 10 determined theauthentication mode as a mode to be executed, the control part 10 shiftsto the authentication mode, and controls the blood vessel imaging part12, similarly to the case of the aforementioned blood vesselregistration mode.

In this case, the blood vessel imaging part 12 performs the drivecontrol of the near infrared light source LS and the image pickup deviceID, and also adjusts the lens position of the optical lens in theoptical system OP and the exposure time of the image pickup device ID,based on an image signal S10 outputted from the above image pickupdevice ID. After the above adjustment, the blood vessel imaging part 12supplies an image signal S20 outputted from the image pickup device IDto the control part 10.

The control part 10 performs edge processing, smoothing processing,binary processing and line thinning processing similar to theaforementioned blood vessel registration mode to the image signal S20,to extract the blood vessels included in the picture of the image signalS20.

Further, the control part 10 reads the registration data D1 registeredin the flash memory 13, and restores the blood vessels based on theposition information and phase information in the above registrationdata D1.

Then, the control part 10 compares these restored blood vessels with theblood vessels extracted from the image signal S20, and determineswhether or not the user who put on his/her finger at the time is aregistered person (regular user), according to the degree of the abovecomparison.

Here, when the user was determined to be the registered person, thecontrol part 10 generates an execution command COM3 to make an operationprocessing apparatus connected to the external interface 14 (not shown)perform a predetermined operation, and transfers this to the operationprocessing apparatus via the external interface 14.

As an embodiment of this operation processing apparatus connected to theexternal interface 14, for example, in the case of adopting a door in alocked state, the control part 10 transfers the execution command COM3to make the door perform an unlocking operation to the door. Further, asother embodiment of the operation processing apparatus, in the case ofadopting a computer in the state that a part of operation mode has beenrestricted in a plurality of operation modes, the control part 10transfers the execution command COM3 to make the computer release therestricted operation mode to the computer.

Note that, two examples have been given as the embodiments, the presentinvention is no only limited to this but also other embodiments can besuitably selected. Further, in this embodiment, it has dealt with casewhere the operation processing apparatus is connected to the externalinterface 14. However, the configuration of software and hardware in theoperation processing apparatus may be built in the authenticationapparatus 1.

On the contrary, when the user was determined not to be the registeredperson, the control part 10 displays that thing on a display part 15 ain the notification part 15, and also performs audio output through anaudio output part 15 b in the notification part 15. Thereby, that theuser was determined not to be the registered person is notified visuallyand by hearing.

In this manner, the control part 10 can execute the authentication mode.

(2) Concrete Processing Contents of First Feature Point ExtractionProcessing

Next, as the feature point extraction processing by the control part 10executed in the registration mode, two concrete processing contents willbe given in this embodiment. First, the concrete processing contents offirst feature point extraction processing will be described.

As shown in FIG. 2, functionally, the first feature point extractionprocessing can be divided into a feature point detecting part 21, acurve point eliminating part 22, an end point eliminating part 23 and afeature point correcting part 24 respectively. Each of these featurepoint detecting part 21, curve point eliminating part 22, and end pointeliminating part 23 and feature point correcting part 24 will bedescribed in detail below.

(2-1) Detection of Feature Point

To the feature point detecting part 21, the processing result of theedge processing, smoothing processing, binary processing and linethinning processing to the image signal S2 outputted from the imagepickup device ID (FIG. 1) is supplied as image data. The blood vesselsincluded in the image of this image data are set to black pixels or theopposite white pixels by the binary processing, and their width(thickness) is set to “1” by the line processing.

This thing that the blood vessel width is “1” means that the bloodvessel width is one pixel, that is, as a result that a line width in theimage data was set to one pixel, a parameter (the number of pixels) inthe orthogonal direction to the circulating direction of the bloodvessels is fixed to a minimum unit, and the blood vessel was representedby a “line”.

The detection processing of a feature point on this blood vessel in onepixel width (hereinafter, this is referred to as a blood vessel line)will be described below by separating stages. However, in thisembodiment, it will be described by assuming the pixels of the bloodvessel as black pixels.

(2-1-1) First Stage

As a first stage, the feature point detecting part 21 detects a branchpoint and an end point to be said as the essence of a feature in a bloodvessel line, from pixels forming the blood vessel line (black pixels).

Concretely, in each of pixels forming an inputted image (image data),the feature point detecting part 21 sets a pixel (black pixels) otherthan a background pixel (white pixel) as an aimed pixel in apredetermined order, and checks the number of black pixels existing inthe pixels in the neighborhood of the above aimed pixel (the total eightpixels of the four pixels in the upper, lower, right and left directionsand the four pixels in the diagonal directions).

Here FIGS. 3A to 3C show the appearance patterns of a black pixelexisting in an end point, a branch point and an isolated point in ablood vessel line, and in pixels in the neighborhood of them. As alsoobvious from FIGS. 3A to 3C, in the case where blood vessels arerepresented in one pixel width, the relationship between and end point,a branch point, and a isolated point in the blood vessel (that is, theblood vessel line), and the “number” of black pixels in the neighborhoodof them becomes significant, and as a branch pattern, it typicallybecomes either three branches or four branches.

For example, as shown in FIGS. 4A to 4C, in the case where one blackpixel exists in the neighborhood of a aimed pixel (FIG. 4A, the featurepoint detecting part 21 detects the aimed pixel as the end point of theblood vessel line. In the case where three black pixels exist in theneighborhood of a aimed pixel (FIG. 4B), or the case where four blackpixels exist in the neighborhood of a aimed pixel (not shown), thefeature point detecting part 21 detects the aimed pixel as a branchpoint. And in the case where a black pixel does not exist in theneighborhood of a aimed pixel (FIG. 4C), the feature point detectingpart 21 detects the aimed pixel as an isolated point.

Then, in thus detected end point, branch point and isolated point, thefeature point detecting part 21 eliminates the isolated point that willnot be a component of the blood vessel line.

In this manner, in the first stage, the feature point detecting part 21detects an end point and a branch point in a blood vessel line,according to the number of black pixels existing in the neighborhood ofthe black pixel set as a aimed pixel.

(2-1-2) Second Stage

Next, as a second stage, the feature point detecting part 21 detects acurve point from the pixels forming the blood vessel line (blackpixels), based on the end point and branch point detected in the firststage.

For example, in the case shown in FIG. 5, the feature point detectingpart 21 sets a branch point DP1 as the start point, and sets otherfeature points appearing following the above branch point DP1 set as thestart point (end point EP1, end point EP2, branch point DP2) as thefinish point (hereinafter, this is referred to as a partial blood vesselline). Similarly, the feature point detecting part 21 tracks a partialblood vessel line, by setting the branch point DP2 as the start point,and setting other feature points (end point EP3), end point EP4)appearing following the above the branch pint DP2 set as the start pointas the finish point.

In the example of this FIG. 5, the branch points DP1, DP2 are set as thestart points, however, an end point may be set as the start point. Inthis connection, as also obvious from FIG. 5, an end point only can betypically either one of the start point and the finish point. However, abranch point can be typically one or both of the start point and thefinish point in overlap.

Here, FIG. 6 shows a concrete tracking scheme. In this FIG. 6, thefeature point detecting part 21 sequentially tracks continuous blackpixels, from the start point to the finish point of the black pixelexisting in the neighborhood of the present aimed pixel, by setting ablack pixel other than the black pixel that was set gas a aimed pixelbefore (pixel represented by horizontal hatching) in the black pixelsexisting in the neighborhood of the present aimed pixel (pixelrepresented by net hatching).

Since this continuous black pixels (partial blood vessel line) is ablood vessel line from a branch point or an end point to the next branchpoint or an end point, a branch does not exist. Therefore, an aimedpixel typically becomes a point on a straight line or a curve point. Inthis connection, FIGS. 7A and 7B show the appearance patterns of blackpixels in the neighborhood of the point on a straight line and the curvepoint.

For example, as shown in FIG. 8, in the tracking process between thestart point and the finish point (pixels represented by diagonal checkhatching), if the linearity of the black pixels before the present aimedpixel is lost from the black pixel set as the next aimed pixel, thefeature point detecting part 21 detects the above present aimed pixel asa curve point (pixel represented by check hatching).

If reaching to the finish point soon, the feature point detecting part21 assigns the feature points from the start point via the curve pointto the finish point in this partial blood vessel line as a group.

In this manner, in the second stage, the feature point detecting part 21tracks the blood vessel line for every partial blood vessel line from abranch point or an end point to the next branch point or an end point,and detects the position that the direction of the above trackingchanges as a curve point. And also the feature point detecting part 21assigns these feature points from the start point via the curve point tothe finish point in the partial blood vessel line as a group.

In the case of this embodiment, as shown in FIGS. 7A and 7B, it isconsidered that the appearance patterns in the neighborhood of a pointon a straight line and a curve point becomes significant. In the featurepoint detecting part 21, a tracking order pattern for a pixel in theneighborhood of a aimed pixel is set according to the positionalrelationship between the present aimed pixel and the pixel that was theaimed pixel preceding to it (hereinafter, this is referred to as animmediately-before aimed pixel).

Concretely, as shown in FIGS. 9A to 9C, tracking order patterns arerespectively set in the cases where an immediately-before aimed pixel(pixel represented by horizontal hatching) is positioned in thehorizontal direction, the vertical direction and the diagonal directionto the present aimed pixel, (pixel represented by net hatching). As alsoobvious from FIGS. 7A to 7B, in the cases where the immediately-beforeaimed pixel is positioned in the horizontal direction or the verticaldirection to the present aimed pixel (FIGS. 9A, 9B), in a blood vesselline in one pixel width, the positions that appears next black pixelbecome a pixel Po1 facing to the immediately-before aimed pixel, andpixels Po2, Po3 adjacent to the pixel Po1. Therefore, in the trackingorder pattern in this case, the above pixel Po1 us set to the first, andthe pixels Po2, Po3 adjacent to the pixel Po1 are set to the second andthe third.

On the other hand, as also obvious from FIGS. 7A and 7B, in the casewhere the immediately-before aimed pixel is positioned in the diagonaldirection to the present aimed pixel (FIG. 9C), in a blood vessel linein one pixel width, in addition to the pixel Po1 facing to theimmediately-before aimed pixel and the pixels Po2, Po3 adjacent to thepixel, the positions that appears next become pixels Po4, Po5 adjacentto the pixels Po2, Po3. Therefore, in the tracking order pattern in thiscase, the above pixel Po1 is set to the first, the pixels Po2, Po3adjacent to the pixel Po1 are set to the second and the third, and thepixels Po4, Po5 adjacent to the pixels Po2, Po3 are set to the fourthand the fifth.

In these tracking order patterns, for example, as shown in FIG. 10, inthe case where the immediately-before aimed pixel is positioned in thediagonal direction to the present aimed pixel, the feature pointdetecting part 21 selects a corresponding tracking order pattern, andtracks a black pixel from a part in the neighborhood of the presentaimed pixel in the order of this tracking order pattern.

In this manner, the feature point detecting part 21 tracks a part ofpixels in the neighborhood of the present aimed pixel in the orderaccording to the positional relationship between the present aimed pixeland the immediately-before aimed pixel. Thereby, a curve point can bedetected at a higher speed, in comparison with the case of uniformlytracking all of the pixels in the neighborhood of the above presentaimed pixel.

(2-2) Elimination of Curve Point

The curve point eliminating part 22 eliminates a curve point as theoccasion demands, by setting feature points from the start point via acurve point to the finish point in a partial blood vessel line that havebeen assigned as a group by the feature point detecting part 21(hereinafter, this is referred to as a partial blood vessel formingsequence) as a processing unit.

In the case of using the blood vessel line in FIG. 5 as an example, asshown in FIG. 11, the partial blood vessel forming sequence is formed bythe start point (branch point) GP_(f1) and finish point (end pointGP_(E1) in a partial blood vessel line BSL₁, a curve point between theabove start point and finish point (not shown), the start point (branchpoint) GP_(f2) and the finish point (end point) GP_(E2) in a partialblood vessel line BSL₂, a curve point between the above start point andfinish point (not shown), the start point (branch point) GP_(f2) and thefinish point (end point) GP_(E2) in a partial blood vessel line BSL₃, acurve point between the above start point and finish point (not shown),the start point (branch point) GP_(f4) and the finish point (end point)GP_(E4) in a partial blood vessel line BSL₄, a curve point between theabove start point and finish point (not shown), and the start point(branch point) GP_(f5) and the finish point (end point) GP_(E5) in apartial blood vessel line BSL₅, and a curve point between the abovestart point and finish point (not shown). The curve points in thesepartial blood vessel forming sequences are eliminated as the occasiondemands. In this connection, although the branch points GP_(f1),GP_(f2), and GP_(f3), GP_(f4) and GP_(f5) in this FIG. 11 are the sameas position (coordinate) information, they belong different groups.Thus, they are shown by separating for convenience.

Because the contents of the elimination processing of the curve pointsin these partial blood vessel forming sequence are the same, the abovecontents will be described about each stage, by limiting to the casewhere a certain partial blood vessel forming sequence is a processingobject.

(2-2-1) First Stage

First, as a first stage, in the case where either one or both of thestart point and the finish point in a partial blood vessel formingsequence are branch points, if there is a curve point in theneighborhood of the branch point, the curve point eliminating part 22eliminates this.

Concretely, for example, as shown in FIG. 12, in the case where thestart point of a partial blood vessel forming sequence forming a partialblood vessel line BSL_(X) is a branch point D_(PX), the curve pointeliminating part 22 eliminates a curve point B_(PX) existing in thepixels surrounding the branch point D_(PX) (the total eight pixels ofthe four pixels in the upper, lower, right and left directions and thefour pixels in the diagonal directions).

Accordingly, the curve point eliminating part 22 selects a curve pointthat is apt to frequently appear many but has the little meaning ofexistence as a feature component, as an elimination object. As a result,for example, as shown in FIG. 13, the curve point eliminating part 22can eliminate a curve point so that the partial blood vessel line afterelimination becomes simple (smooth), as well as approximating the formof the partial blood vessel line after elimination to the partial bloodvessel line before elimination.

In this connection, in the example of FIG. 12, the neighborhood of thebranch point D_(PX) is set as the neighborhood of the branch pointD_(PX). However, instead of this, it may be set as a predetermineddistance area from the branch point D_(PX). Also in this case, thesimilar result as the case of the example of FIG. 12 can be obtained.

In this manner, in the first stage, the curve point eliminating part 22aims to reduce data amount by eliminating a curve point existing in the“neighborhood” of a branch point.

Note that, in comparison with the case of executing eliminationprocessing after a second stage without executing the eliminationprocessing on this first stage, the curve point eliminating part 22 canfurther accurately eliminate a curve point after the above second stage.This has been obvious by experiment results by the present applicant. Ason of the reasons, it is considered that by the presence of a curvepoint in the neighborhood of a branch point, other curve point whichprimarily should be a feature component is hidden.

(2-2-2) Second Stage

Next, as the second stage, in the case where in the partial blood vesselforming sequence, a segment formed by continuous three feature points isclose to a straight line, the curve point eliminating part 22 eliminatesthe middle one of the above three feature points. As a condition todetermine whether or not being close to a straight line as the above, acosine formed by the continuous three feature points and the area of aparallelogram formed by these feature points are adopted. In thisconnection, although the both ends of such continuous three points aresometimes to be a branch point or an end point, the middle feature pointis always to be a curve point.

Here, if it is only conditioned on a cosine formed by continuous threefeature points, for example, as shown in FIGS. 14A and 14B, when thearea of the parallelogram formed by the middle feature point GP_(C) andthe feature points of the both ends GP_(E−1), GP_(E−2) (area representedby hatching) is small (FIG. 14A), even if the middle feature pointGP_(C) is eliminated, the state of the blood vessel line afterelimination is not quite different from the blood vessel line beforeelimination by the elimination.

However, when the area of the parallelogram formed by the middle featurepoint GP_(C) and the feature points of the both ends GP_(E−1), GP_(E−2)is large (FIG. 14B), if the middle feature point GP_(C) is eliminated,the state of the blood vessel line after elimination is quite differentfrom the blood vessel line before elimination by the elimination.

In this manner, not only simply conditioning on the size of a cosineformed by continuous three feature points, by also adding the size ofthe area of the parallelogram formed by the above three feature pointsas the condition, a curve point can be accurately selected as anelimination object by that the partial blood vessel line afterelimination can be smoothed, as well as approximating the forms of thepartial blood vessel line before elimination and the partial bloodvessel line after elimination.

Concretely, the elimination processing of a curve point in this secondstage is executed in a procedure shown in a flowchart of FIG. 15, fromthe start point in the partial blood vessel forming sequence. That is,the curve point eliminating part 22 selects continuous three featurepoints as the present aimed object (step SP1).

Then, for example, as shown in FIG. 16, in the three feature points setas the present aimed object (hereinafter, these are referred to as thepresent aimed continuous three points) GP_(i−1), GP_(i), GP_(i+1) (i=2,3, . . . , m (m is an integer)), the curve point eliminating part 22obtains the absolute value of the outer product of a vector B1 betweenthe feature point of one end GP_(i−1) and the middle feature pointGP_(i), and a vector B2 between the middle feature point GP_(i) and thefeature point of the other end GP_(i+1) (step SP2), and determineswhether or not the absolute value is smaller than a predeterminedthreshold value (hereinafter, this is referred to as an outer thresholdvalue) (step SP3).

Here, if it is above the outer threshold value, this means that the areaof a parallelogram formed by the present aimed continuous three pointsGP_(i−1), GP_(i), GP_(i+1) is large. In this case, the curve pointeliminating part 22 shifts the present aimed object for one point, fromthe start point side to the finish point side of the partial bloodvessel forming sequence (step SP4), and determines whether or not to beable to select continuous three feature points that should be set as thepresent aimed object next (step SP5).

On the contrary, if it is smaller than the outer threshold value, thatis, if the area of the parallelogram formed by the present aimedcontinuous three points GP_(i−1), GP_(i), GP_(i+1) is small, the curvepoint eliminating part 22 obtains the cosine θ_(i) of the above aimedcontinuous three points GP_(i−1), GP_(i), GP_(i+1) (step SP6), andtemporarily stores the cosine θ₁ and the middle feature point GP_(i) byconnecting with each other (step SP7). Then, the curve point eliminatingpart 22 shifts the present aimed object for one point, from the startpoint side to the finish point side of the partial blood vessel formingsequence (step SP4), and determines whether or not to be able to selectcontinuous three feature points that should be set as the present aimedobject next (step SP5).

In this manner, as to the partial blood vessel forming sequence, thecurve point eliminating part 22 sequentially selects continuous threefeature points as an aimed object, by shifting from the start point tothe finish point of the partial blood vessel forming sequence for onepoint. And if the absolute value of the outer product of the vectors B1and B2 in the present aimed continuous three points GP_(i−1), GP_(i),GP_(i+1) selected at the time is smaller than the outer productthreshold value, the curve point eliminating part 22 temporarily storesthe cosine θ₁ in the present aimed continuous three points GP_(i−1),GP_(i), GP_(i+1) (FIG. 16) by connecting with each other (stepsSP1-SP7).

And then, if it becomes impossible to select the next continuous threepoints, the curve point eliminating part 22 determines whether or not inthe cosines that have been temporarily stored until the time, thesmallest cosine is smaller than a predetermined threshold value(hereinafter, this is referred to as a cosine threshold) (step SP8).

Here, if it is smaller than the cosine threshold value, this means thatthe linearity of the line formed by continuous three feature points ishigh. In this case, the curve point eliminating part 22 eliminates themiddle one of the three feature points connected with the smallestcosine (step SP9). And then, the curve point eliminating part 22 repeatsagain the aforementioned processing, from the start point in the partialblood vessel forming sequence until there are not three feature pointsforming a cosine smaller than the cosine threshold value in the partialblood vessel forming sequence.

$\begin{matrix}{{GP}_{D} = \frac{{{PD}\;{1 \cdot {GP}_{j}}} + {{PD}\;{2 \cdot {GP}_{j + 1}}}}{{{PD}\; 1} + {{PD}\; 2}}} & (1)\end{matrix}$

On the contrary, if it is larger than the cosine threshold, that is, ifthere are no three feature points forming a smaller cosine than thecosine threshold value in the partial blood vessel forming sequence, thecurve point eliminating part 22 finishes the elimination processing onthis second stage.

The curve point eliminating part 22 executes the elimination processingof a curve point on the second stage by the above procedure.

In this connection, in the elimination processing in FIG. 16, as theprocedure, in continuous three feature points in the partial bloodvessel forming sequence, one in that the absolute value of the outerproduct of the vectors B1 and B2 (FIG. 16) is smaller than the outerproduct threshold value is previously selected, and if the smallestcosine θ₁ in the cosine θ₁ in the above selected three feature points(FIG. 16) is smaller than the cosine threshold value, the middle one ofthe three feature points connected with the smallest cosine θ₁ iseliminated. However, instead of this, one in that the cosine in theabove three feature points is smaller than the cosine threshold value ispreviously selected, and if the smallest absolute value in the absolutevalues of the outer products of the above selected three feature pointsis smaller than the outer product threshold value, the middle one of thethree feature points connected with the smallest absolute value may beeliminated.

This means that the condition that the absolute value of the outerproduct of the vectors B1 and B2 (FIG. 16) in the present aimedcontinuous three points GP_(i−1), GP_(i), GP_(i+1) (FIG. 16) is smallerthan the outer product threshold value, or the condition that the cosineθ₁ in the above present aimed continuous three points GP_(i−1), GP_(i),GP_(i+1) is smaller than the cosine threshold value (FIG. 16) may be setas the condition for selecting three feature points to be proposed foran elimination object, and also it may be set as the condition fordetermining three feature points that should be set as an eliminationobject from among the three feature points proposed for selection.

In any case, since it is conditioned on the cosine formed by continuousthree feature points and the area of the parallelogram formed by theabove three feature points, as also described with reference to FIGS.14A and 14B, the curve point eliminating part 22 accurately selects themiddle feature point GP_(C) of three feature pointsGP_(E−1)-GP_(C)-GP_(E−2) having the highest linearity, in continuousthree feature points in the partial blood vessel forming sequence, as anelimination object.

As a result, the curve point eliminating part 22 can eliminate a curvepoint so that the partial blood vessel line after elimination becomessimple (smooth), as well as approximating the form of the partial bloodvessel line after elimination to the partial blood vessel line beforeelimination.

In this manner, on the second stage, the curve point eliminating part 22aims to reduce data amount, in three feature points satisfying one ofthe condition that the absolute value of the outer product of vectors incontinuous three feature points in the partial blood vessel formingsequence is smaller than the outer product threshold value, and thecondition that the cosine in the above three feature points is smallerthan the cosine value, by eliminating the middle one of the threefeature points satisfying the other one of the above conditions andbeing the smallest.

Note that, the curve point eliminating part 22 repeatedly executes theprocessing for eliminating a curve point in a part having the highestlinearity in the overall partial blood vessel forming sequence as a soleelimination object. Thus, a curve point of an elimination object in thepartial blood vessel forming sequence can be selected from a generalviewpoint not locally, in comparison with the case of adopting theprocessing that simultaneously watches the condition that the absolutevalue of the outer product of vectors in continuous three feature pointsin the partial blood vessel forming sequence is smaller than the outerproduct threshold value, and the condition that an internal angle formedby the above three feature points is smaller than a prescribed value,and immediately eliminates the corresponding curve point every time whenthe above conditions are satisfied. Therefore, the curve point can befurther accurately eliminated.

(2-2-3) Third Stage

Next, as a third stage, in the case where in the partial blood vesselforming sequence, a segment connecting continuous two feature points isshorter than a prescribed value, for example, as sown in FIGS. 17A and17B, the curve point eliminating part 22 replaces feature pointsGP_(X−1), GP_(X−2) forming the short segment to a new feature pointGP_(N−1), GP_(N−2), according to the form of a blood vessel lineGP_(Y−1)-GP_(X−1)-GP_(X−2)-GP_(Y−2) that connects four feature pointsincluding the feature points GP_(Y−1), GP_(Y−2) connected to the featurepoints GP_(X−1), GP_(X−2) forming the above short segment. In thisconnection, although the both ends of the continuous four feature pointsare sometimes to be a branch point or an end point, the two featurepoints GP_(X−1), GP_(X−2) to be a replacement object are typically to becurve points.

Here, as giving as the examples of these FIGS. 17A and 17B, the form ofthe blood vessel line GP_(Y−1)-GP_(X−1)-GP_(X−2)-GP_(Y−2) connecting thecontinuous four feature points becomes almost either a “Z” form or a “U”form. In the case of having the “Z” form, the curve point eliminatingpart 22 sets a point internally divided by the ratio of the area A1 ofthe parallelogram formed by the feature point GP_(X−1). GP_(X−2) formingthe short segment and the feature point GP_(Y−1) connected to one ofthis, to the area A2 of the parallelogram formed by the above featurepoints GP_(X−1), GP_(X−2) and the feature point GP_(Y−2) connected tothe other end of this, as a new feature point GP_(N−1), and makes theform of a blood vessel line GP_(Y−1)-GP_(N−1)-GP_(Y−2) connecting theabove three feature points into an “I” form.

On the other hand, in the case of having the “U” form, the curve pointeliminating part 22 sets the intersection of the prolongation line ofthe segments GP_(Y−1)-GP_(X−1), GP_(Y−2)-GP_(X−2) connecting the featurepoints GP_(X−1), GP_(X−2) forming the short segment and thecorresponding feature points GP_(Y−1), GP_(Y−2) connected to this, as anew feature point GP_(N−2), and makes the form of a blood vessel lineGP_(Y−1)-GP_(N−2)-GP_(Y−2) connecting the above three feature pointsinto a “V” form.

As also obvious from FIGS. 17A and 17B, not only aiming at the twofeature points GP_(X−1), GP_(X−2) forming the short segment, by addingthe positions of the feature points GP_(Y−1), GP_(Y−2) connected to theabove two feature points GP_(X−1), GP_(X−2) in consideration, andgenerating new feature points GP_(N−1), GP_(N−2), a curve point can beaccurately selected as an elimination object by that the partial bloodvessel line after elimination can be simplified (smoother), as well asapproximating the forms of the partial blood vessel line beforeelimination and the partial blood vessel line after elimination.

The elimination processing of a curve point on this third stage isexecuted in a procedure shown in a flowchart of FIG. 18, from the secondfeature point in the partial blood vessel forming sequence. That is, thecurve point eliminating part 22 selects continuous two feature points asthe present aimed object (step SP11).

Then, if the other end of the two feature points being the present aimedobject does not reach the finish point of the partial blood vesselforming sequence (step SP12), the curve point eliminating part 22determines whether or not the segment between the two feature pointsbeing selected at the time is smaller than a predetermined thresholdvalue (hereinafter, this is referred to as a first segment thresholdvalue) (step SP13). If it is above the first segment threshold value,the curve point eliminating part 22 shifts the present aimed object forone point, from the start point side to the finish point side of thepartial blood vessel forming sequence (step SP14).

In this manner, the curve point eliminating part 22 sequentially selectscontinuous two feature points until selecting the two feature pointssatisfying the condition that the segment is smaller than the firstsegment threshold value, by shifting for one point from the start pointto the finish point of the partial blood vessel forming sequence (stepsSP11-SP14).

On the contrary, if the segment between the two feature points issmaller than the first segment threshold value, for example, as shown inFIG. 19, the curve point eliminating part 22 obtains the outer productof a vector B10 between the feature points GP_(j) (j=2, 3, . . . , n (nis an integer)) and GP_(j+1) being the present aimed object and a vectorB11 between the feature point GP_(j) and a feature point GP_(j−1)connected to one end side of the feature point GP_(j). Further, thecurve point eliminating part 22 obtains the outer product of the vectorB10 between the two feature points GP_(j) and GP_(j+1) being the presentaimed object, and a vector B12 between the feature point GP_(j+1) and afeature point GP_(j+2) connected to the other end side of the featurepoint GP_(j+1) (step SP15). Then, the curve point eliminating part 22determines whether or not the signs of positive and negative in theouter product of the vectors B10 and B11 and the outer product of thevectors B11 and B12 agree (step SP16).

Here, if the signs of positive and negative does not agree, as shown inthis example of FIG. 19, this means that the form of a segmentGP_(j−1)-GP_(j)-GP_(j+1)-GP_(j+2) connecting the two feature pointsGP_(j), GP_(j+1) being the present aimed object and the feature pointsGP_(j−1), GP_(j+2) connected to this precedingly and followingly is a“Z” form.

In this case, the curve point eliminating part 22 sets the absolutevalue of the outer product of the vectors B10 and B11 (that is, the areaTa of a parallelogram formed by the feature points GP_(j−1), GP_(j),GP_(j+1)) as “PD1”, and also sets the absolute value of the outerproduct of the vectors B10 and B12 (that is, the area Tb of aparallelogram formed by the feature points GP_(j), GP_(j+1), GP_(j+2))as “PD2”, and obtains a dividing point GP_(D) that internally dividesinto the areas Ta:Tb (step SP17), according to the following equation(step SP17):

$\begin{matrix}{{GP}_{D} = \frac{{{PD}\;{1 \cdot {GP}_{j}}} + {{PD}\;{2 \cdot {GP}_{j + 1}}}}{{{PD}\; 1} + {{PD}\; 2}}} & (1)\end{matrix}$Then, the curve point eliminating part 22 generates the dividing pointGP_(D), and also eliminates the two feature points GP_(j), GP_(j+1)being the present aimed object (step SP18), and then shifts the presentaimed object for one point from the start point side to the finish pointside of the partial blood vessel forming sequence (step SP14), andrepeats the aforementioned processing.

On the contrary, if the signs of positive and negative agree, forexample, as shown in FIG. 20, this means that the form of a segmentGP_(j−1)-GP_(j)-GP_(j+1)-GP_(j+2) connecting the two feature pointsGP_(j), GP_(j+1) being the present aimed object and the feature pointsGP_(j−1), GP_(j+2) connection to this precedingly and followingly is a“U” form.

In this case, the curve point eliminating part 22 sets the outer productof the vectors B10 and B12 as “PD3”, and sets the outer product of thevectors B11 and B12 as “PD4”, and obtains an intersection GP_(IN) on theprolongation lines of the vectors B11 and B12, according to thefollowing equation (step SP19):

$\begin{matrix}{{GP}_{IN} = {{GP}_{j} + {{\frac{{PD}\; 3}{{PD}\; 4} \cdot B}\; 10}}} & (2)\end{matrix}$Then, the curve point eliminating part 22 generates the intersectionGP_(IN), and also eliminates the two feature points GP_(j), GP_(j+1)being the present aimed object (SP18), and then shifts the present aimedobject for one point from the start point side to the finish point sideof the partial blood vessel forming sequence (step SP14), and repeatsthe aforementioned processing.

The curve point eliminating part 22 executes the elimination processingof a curve point on the third stage by the above procedure.

As also described in FIGS. 17A and 17B, the curve point eliminating part22 adds in consideration the positions of the feature points GP_(Y−1),GP_(Y−2) connected to the continuous three feature points GP_(X−1),GP_(X−2) precedingly and followingly. Therefore, the two feature pointsGP_(X−1), GP_(X−2) that should be set to an elimination object can beaccurately replaced to a new feature point GP_(N−1), GP_(N−2).

As a result, the curve point eliminating part 22 can eliminate a curvepoint so that the partial blood vessel line after elimination becomessimple (smooth), as well as approximating the form of the partial bloodvessel line after elimination to the partial blood vessel line beforeelimination.

In this manner, on the third stage, the curve point eliminating part 22aims to reduce data amount by replacing the two feature points GP_(X−1),GP_(X−2) satisfying the condition that the segment GP_(X−1)-GP_(X−2)connecting continuous two feature points in the partial blood vesselforming sequence is smaller than the first segment threshold value, tothe dividing pint GP_(D) that internally divides the segment at theratio of the area Ta formed by the two feature points and a featurepoint connected to one of the two feature points to the area Tb formedby the above two feature points and a feature point connected to theother of the two feature points, or to the intersection GP_(IN) of aprolongation line connecting one of the two feature points and a featurepoint connected to this and a prolongation line connecting the other ofthe above two feature points and a feature point connected to this.

Note that, the curve point eliminating part 22 switches the point to bereplaced (GP_(D) or GP_(IN)) according to a difference in signs ofpositive and negative in the outer product of the continuous two featurepoints and a feature point connected to one of the two feature points,and the outer product of the above two feature points and a featurepoint connected to the other of the two feature points. That is, featurepoints can be accurately replaced by adding in consideration theconnection state of the feature points GP_(Y−1), GP_(Y−2) connected tothe continuous two feature points GP_(X−1), GP_(X−2) precedingly andfollowingly.

(2-2-4) Fourth Stage

Finally, as a fourth stage, as to the partial blood vessel formingsequence, if the area of a parallelogram formed by continuous threefeature points is smaller than a prescribed value, the curve pointeliminating part 22 eliminates the middle feature point. In thisconnection, the both ends of the continuous three feature points aresometimes to be a branch point or an end point, however, the middlefeature point is typically to be a curve point.

Here, whereas on the second stage, the linearity is took into account byalso adding in consideration the size of the cosine of a parallelogramformed by continuous three feature points, on this fourth stage, thelinearity is not took into account, and if the area of the parallelogramis smaller than a prescribed value, the curve point is eliminated.

This is because in the elimination processing on the second and thethird stages, a curve pint is eliminated by broadly grasping withoutgoing into the particulars of the partial blood vessel forming sequence,thus when the above elimination processing was finished, the part inthat the area of the parallelogram formed by continuous three featurepoints in the partial blood vessel forming sequence is smaller than aprescribed value is almost limited to that curve points are not muchaway and are heavily concentrated, so that even if a curve point in thispart is set as an elimination object, the state of the blood vessel lineafter elimination does not become quite different from the blood vesselline before elimination.

Concretely, the elimination processing of a curve point on the fourthstage is executed in a procedure shown in a flowchart of FIG. 21, fromthe start point in a partial blood vessel forming sequence. That is, thecurve point eliminating part 22 selects continuous three feature pointsas the present aimed object (step SP21).

Then, for example, as shown in FIG. 22, in the present aimed continuousthree points (three feature points set as the present aimed object)GP_(k−1), GP_(k), GP_(k+1) (k=2, 3, . . . , s (s is an integer)), thecurve point eliminating part 22 obtains the absolute value of the outerproduct of a vector B1 between a feature point at one end GP_(k−1) andthe middle feature point GP_(k), and a vector B2 between the middlefeature point GP_(k) and a feature point at the other end GP_(k+1) (stepSP22), and temporarily stores this absolute value of the outer productand the present aimed continuous three points GP_(k−1), GP_(k), GP_(k+1)(position information) by connecting with each other (step SP23).

Then, the curve point eliminating part 22 shifts the present aimedobject for one point, from the start point side to the finish point sideof the partial blood vessel forming sequence (step SP24), and determineswhether or not to be able to select continuous three feature points thatshould be set as the present aimed object next (step SP25).

In this manner, as to the partial blood vessel forming sequence, thecurve point eliminating part 22 sequentially selects an aimed object tothe finish point, by shifting continuous three feature points for onepoint from the start point of the partial blood vessel forming sequence,and temporarily stores the area of the parallelogram formed by thepresent aimed continuous three points GP_(k−1), GP_(k), GP_(k+1)selected at the time (FIG. 22) (the absolute value of the outer productof the vectors B1 and B2), and the present aimed continuous three pointsGP_(k−1), GP_(k), GP_(k+1) (FIG. 16) selected at the time by connectingwith each other (steps SP21-SP25).

Then, if it becomes impossible to select the next continuous threefeature points, in the absolute values of the outer product that havebeen temporarily stored until the time, the curve point eliminating part22 determines whether or not the absolute value of the smallest outerproduct is smaller than a predetermined threshold value (hereinafter,this is referred to as a second outer product threshold value) (stepSP26).

Here, if the absolute value is smaller than the second outer productthreshold value, the curve point eliminating part 22 eliminates themiddle feature point GP_(k) in the three feature points GP_(k−1),GP_(k), GP_(k+1) (FIG. 22) connected to the smallest absolute value ofthe smallest outer product (step SP27). And then, the curve pointeliminating part 22 repeats the aforementioned processing again from thestart point in the partial blood vessel forming sequence, until thereare not three feature points that form a smaller cosine than a cosinethreshold value in the partial blood vessel forming sequence.

On the contrary, if the absolute value is larger than the second outerproduct threshold value, that is, if there became no three featurepoints forming a smaller area than the second outer product thresholdvalue in the partial blood vessel forming sequence, the curve pointeliminating part 22 finishes the elimination processing on the fourthstage.

The curve point eliminating part 22 executes the elimination processingof a curve point on the fourth stage by the above procedure.

Therefore, in the partial blood vessel forming sequence, the curve pointeliminating part 22 sets the part in that curve points are not much awayand the distribution is heavily concentrated as an elimination object.As a result, the curve point eliminating part 22 can select a curvepoint as an elimination object so that the partial blood vessel lineafter elimination becomes simple (smooth), as well as approximating theform of the partial blood vessel line after elimination to the partialblood vessel line before elimination.

In this manner, on the fourth stage, in the areas of parallelogramsformed by continuous three feature points in the partial blood vesselforming sequence, the curve point eliminating part 22 aims at reducingdata amount, by eliminating the middle feature point in the threefeature points in that the area is the smallest and is smaller than aprescribed value.

Note that, similarly to the second stage, the curve point eliminatingpart 22 repeatedly executes the processing for eliminating a curve pointin the part forming the smallest area in the overall partial bloodvessel forming sequence as a sole elimination object. Therefore, it ispossible to select a curve point being an elimination object in thepartial blood vessel forming sequence from a general viewpoint notlocally. Thus, the curve point can be further accurately eliminated, incomparison with the case of adopting the processing that “eliminates themiddle one of three feature points every time when satisfying thecondition that the area of the parallelogram formed by the continuousthree feature points in the partial blood vessel forming sequence issmaller than the prescribed value”.

(2-3) Elimination of End Point

The end point eliminating part 23 eliminates the start point or thefinish point of the partial blood vessel forming sequence in eachpartial blood vessel line as the occasion demands. This eliminationprocessing of the start point or the finish point of the partial bloodvessel forming sequence will be described below, by separating stages.

(2-3-1) First Stage

As a first stage, for example, as shown in FIG. 23, in the case whereeither one or both of the start point and the finish point in thepartial blood vessel forming sequence is an end point, if the distancebetween the end point DPx and a curve point Px connected to the aboveend point DPx is shorter than a predetermined threshold value, the endpoint eliminating part 23 eliminates the end point DPx.

Accordingly, the end point eliminating part 23 sets an end point that ispoor in the meaning of presence as a feature component as an eliminationobject. As a result, the end point eliminating part 23 can eliminate anend point so that the partial blood vessel line after eliminationbecomes simple (smooth), as well as approximating the form of the bloodvessel line after elimination to the blood vessel line beforeelimination.

In this manner, on the first stage, the end point eliminating part 23aims at reducing data amount, by eliminating the end point in that thedistance to a curve point connect to this is short in end points. Inthis connection, in this embodiment, an elimination object is defined asan end point, however, it may be a curve point connected to the endpoint. Thereby, the same effect as the case of using an point as anelimination object can be obtained.

(2-3-2) Second Stage

Next, as a second stage, if there is a pair of partial blood vessellines in that the intersection angle of three or four partial bloodvessel lines extending from a branch point in branch points on a bloodvessel line is close to 180 degrees, the end point eliminating part 23assigns a partial blood vessel forming sequence in the one pair ofpartial blood vessel line as one partial blood vessel forming sequence,and eliminates one of the start point and the finish point being the endpoints of the original partial blood vessel forming sequence. In thisconnection, as also described with reference to FIGS. 3A to 3C, in ablood vessel (blood vessel line) in one pixel width, partial bloodvessel lines extending from a branch point become typically three orfour.

Concretely, for example, as shown in FIG. 24, in the case where threepartial blood vessel lines PBL_(A), PBL_(B), PBL_(C) are extended from abranch point GP (GP_(A1), GP_(B1), GP_(C1)), the end point eliminatingpart 23 obtains, in these partial blood vessel lines PBL_(A), PBL_(B),PBL_(C), the cosine (cos(θ_(A−B)), (cos(θ_(A−C)), (cos(θ_(B−C))) of theintersection angles θ_(A−B), θ_(A−C), θ_(B−C) of a pair of partial bloodvessel lines.

Here, when the smallest cosine cos(θ_(A−B)) is smaller than a secondcosine threshold value, this means that the intersection angle of thepartial blood vessel line is closer to 180 degrees. At this time, in theboth ends of the partial blood vessel forming sequences GP_(A1),GP_(A2), . . . , GP_(A−end) and GP_(B1), GP_(B2), . . . , GP_(B−end) ofa pair of partial blood vessel lines corresponding to the smallestcosine cos(θ_(A−B)), the end point eliminating part 23 sets the pointsGP_(A−end), GP_(B−end) that are not overlapped as the start point or anend point, and reassigns the feature points between the start point andthe end point as one group.

As a result, the one pair of blood vessel lines PBL_(A), PBL_(B) areconnected. Therefore, for example, as shown in FIG. 24, if comparing tothe partial blood vessel forming sequence of the one pair of partialblood vessel lines before connecting, the number of the partial bloodvessel forming sequences GP_(AB−first), . . . , GP_(AB10), GP_(AB11),GP_(AB12), . . . , GP_(AB−end) of the above connected partial bloodvessel lines PBL_(AB) reduces for one point, by that the two branchpoints GP_(A1), GP_(B1) that were the respective start points of thepartial blood vessel lines of the above one pair of partial blood vessellines were replaced to one intermediate point GP_(AB11). Note that,since the partial blood vessel line PBL_(AB) is that the one pair ofpartial blood vessel lines PBL_(A), PBL_(B) were simply connected, theform of the blood vessel line does not change between before and afterconnecting.

On the contrary, when the smallest cosine cos(θ_(A−B)) is larger thanthe second cosine threshold value, the end point eliminating part 23does not reassigning a group. If there is a branch point that has notbeen a processing object yet, the end point eliminating part 23 shifts aprocessing object to the next branch point, and if there is no branchpoint that has not been a processing object yet, the end pointeliminating part 23 finishes this processing.

On the other hand, for example, as shown in FIG. 25, in the case wherefour partial blood vessel forming sequences PBL_(A), PBL_(B), PBL_(C),PBL_(D) are extended from the branch point GP (GP_(A1), GP_(B1),GP_(C1), GP_(D1)), in these partial blood vessel forming sequencesPBL_(A), PBL_(B), PBL_(C), PBL_(D), the end point eliminating part 23obtains the cosines (cos(θ_(A−B)), cos(θ_(A−C)), cos(θ_(A−D)),cos(θ_(B−C)), cos(θ_(B−D)), cos(θ_(C−D)), of the intersection anglesθ_(A−B), θ_(A−C), θ_(A−D), θ_(B−C), θ_(B−D), θ_(C−D) of a pair ofpartial blood vessel lines.

Here, when the smallest cosine cos(θ_(B−D)) is smaller than a secondcosine threshold value, this means that the intersection angle of thepartial blood vessel line is close to 180 degrees. At this time, in theboth ends of the partial blood vessel forming sequences GP_(B1),GP_(B2), . . . , GP_(B−end) and GP_(D1), GP_(D2), . . . , GP_(D−end) ofa pair of partial blood vessel lines corresponding to the smallestcosine cos(θ_(B−D)), the end point eliminating part 23 sets the pointsGP_(B−end), GP_(D−end) that are not overlapped as the start point or anend point, and reassigns the feature points between the start point andthe end point as one group.

As a result, the one pair of blood vessel lines PBL_(B), PBL_(D) areconnected. Therefore, for example, as shown in FIG. 25, if comparing tothe partial blood vessel forming sequence of the one pair of partialblood vessel lines before connecting, the number of the partial bloodvessel forming sequences GP_(BD−first), . . . , GP_(BD10), GP_(BD11),GP_(BD12), . . . , GP_(BD−end) of the above connected partial bloodvessel line PBL_(BD) reduces for one point, by that the two branchpoints GP_(B1), GP_(D1) that were the respective start points of thepartial blood vessel lines of the above one pair of partial blood vessellines were replaced to one intermediate point GP_(BD11). Note that,since the partial blood vessel line PBL_(BD) is that the one pair ofpartial blood vessel lines PBL_(B), PBL_(D) were simply connected, theform of the blood vessel line does not change between before and afterconnecting.

In the case of this four branches, even if the one pair of partial bloodvessel lines PBL_(B), PBL_(D) were connected, the partial blood vessellines PBL_(A), PBL_(C) that have not been connected yet remain. However,when the cosine (cos(θ_(A−C))) of the intersection angle θ_(A−C) of theremaining partial blood vessel lines PBL_(A), PBL_(C) is smaller thanthe second cosine threshold value, for example, as shown in FIG. 25, theend point eliminating part 23 replaces the respective partial bloodvessel forming sequences of these partial blood vessel lines PBL_(A),PBL_(C) to one partial blood vessel forming sequence GP_(AC−first), . .. , GP_(AC10), GP_(AC11), GP_(AC12), . . . , GP_(AC−end), similarly tothe partial blood vessel forming sequences of the partial blood vessellines PBL_(B), PBL_(D), and eliminates one of the start points GP_(A1)and GP_(C1) being the end points of the original partial blood vesselforming sequence.

On the contrary, when the smallest cosine cos(θ_(A−B)) is larger thanthe second cosine threshold value, the end point eliminating part 23does not reassigns a group. If there is a branch point that has not beena processing object yet, the end point eliminating part 23 shifts aprocessing object to the next branch point, and if there is no branchpoint that has not been a processing object yet, the end pointeliminating part 23 finishes this processing.

In this connection, although the points that a part of them isoverlapped in FIGS. 24 and 25 are the same as position (coordinate)information, they are different in group. Thus, they are shownseparately for convenience.

In this manner, on the second stage, in branch points on a blood vesselline, the end point eliminating part 23 replaces partial blood vesselforming sequences in the one pair of partial blood vessel linessatisfying the condition that the cosine of the intersection angle ofpartial blood vessel lines extending from the above branch point issmaller than the second cosine threshold value to one partial bloodvessel forming sequence, and eliminates one of the start point and thefinish point to be the end points of the original partial blood vesselforming sequence. Thereby, data amount can be reduced.

(2-4) Correction of Feature Point

The feature point correcting part 24 properly changes the positions offeature points that were remained as the aforementioned variouselimination processing results so that a segment connecting the abovefeature points most approximate to the original blood vessel line(hereinafter, this is referred to as an original blood vessel line).

This straight line connecting the remained feature points becomes ablood vessel line that can be restored in authentication. Here, in theaforementioned various elimination processing, a feature point waseliminated so that the partial blood vessel line after eliminationbecomes simple (smooth), as well as approximating the form the partialblood vessel line after elimination to the partial blood vessel linebefore elimination. Thus, the straight line connecting the remainingfeature points (hereinafter, this is referred to as a restoration objectblood vessel line) is not vastly different from a characteristic formpattern in the original blood vessel line.

However, for example, as shown in FIG. 26, there is a case where thepositions of the pixel of a restoration object blood vessel line (shownby a circle in the figure) and the pixel of an original blood vesselline (shown by a square in the figure) are slightly different. Thisdifference does not particularly cause a problem when in simply used inreducing or enlargement of a map or the like. However, it might cause aproblem when in used in bioauthentication or the like.

Then, in this embodiment, this correction processing of a feature pointis adopted in order to make sure the approximation of a restorationobject blood vessel line to an original blood vessel line.

Concretely, for example, as shown in FIG. 27, in remaining featurepoints, two feature points PX1, PX2 that form a segment being thelongest in segments connecting mutually connected feature points are setas the present change object, and selects one of the feature points PX1and point Pad1 surrounding it (the total eight pixels of the four pixelsin the upper, lower, right and left directions and the four pixels inthe diagonal directions), and the total nine positions of the otherfeature point PX2 and points Pad2 surrounding it, as positions proposedfor change.

Then, the feature point correcting part 24 searches for a positioncorresponding to the segment in that the number of passing through apixel in the original blood vessel line is the largest, in 81 patternsof segments SEG connecting mutual positions proposed for change, fromthe positions proposed for change, by using the Bresenham algorithm, forexample.

As the search result, if a position corresponding to the segment in thatthe number of passing through a pixel in the original blood vessel lineis the largest is detected, the feature point correcting part 24 movesthe two feature points PX1, PX2 being the present change object to theabove position. As a result, as shown in FIG. 28, as also obvious bycomparing to FIG. 26 showing before change, a segment connecting featurepoints PX11, PX12 after change more approximates to the pixel of thecorresponding original blood vessel line, than the segment connectingthe feature points PX1, PX2 before change.

Then, as shown in FIG. 29, the feature point connecting part 24 setsfeature points PX21, PX22 connected to the feature points after changePX11, PX12 as the present change object, and selects the total ninepositions of the feature points PX21, PX22 and points around them Pad1,Pad2 respectively, as a position proposed for change.

Then, the feature point correcting part 24 searches for a positioncorresponding to the segment in that the number of passing through apixel in the original blood vessel line is the largest, respectively in9 patterns of segment SEG11, SEG12 connecting the feature points afterchange PX11, PX12 and the positions proposed for change, from thepositions proposed for change.

As the search result, if a position corresponding to the segment in thatthe number of passing through a pixel in the original blood vessel lineis the largest is detected, the feature point correcting part 24 movesthe feature points PX21, PX22 being the present change object,respectively to the above position. As a result, as shown in FIG. 30, asalso obvious by comparing to FIG. 26 showing before change, a segmentconnecting feature points after change PX31, PX32 more approximate tothe pixel of the corresponding original blood vessel line, than thesegment connecting the feature points before change PX21, PX22. In thisconnection, in the example of this FIG. 30, the feature point afterchange PX31 becomes (moving to) the same position as the position of thefeature point before change PX21.

Further, in the case where the feature points after change PX31, PX32are not end points, the feature point correcting part 24 sequentiallyselects a feature point being connected next as the present changeobject until to the finish end of the blood vessel line, and in thepositions of the feature point being the present change object and inits neighborhood, moves the feature point being the present changeobject to a position corresponding to the segment in that the number ofpassing through a pixel in the original blood vessel line is the largestin the segments connected to the feature point that was the presentchange object preceding to the above present change object.

In this connection, in the example of FIGS. 27 to 30, the feature pointbeing the present change object and the points surrounding it are set asthe positions proposed for change. However, instead of this, the featurepoint being the present change object and a predetermined distance areafrom the feature point may be set as the position proposed for change.That is, the feature point being the present change object and points inthe neighborhood of it can be set as the position proposed for change.Also in this case, the same effect as the case of the example of FIGS.27 to 30 can be obtained.

In this manner, the feature point correcting part 24 sequentiallyselects a feature point on the blood vessel line as the present changeobject, from a pair of feature points forming the longest segment to thefinish end of the blood vessel line, and moves the feature pointselected as the above present change object to a position correspondingto the segment in that the number of passing through a pixel in theoriginal blood vessel line is the largest, in the positions of thefeature point and its neighborhood. Thereby, the restoration objectblood vessel line can be further approximated to the original bloodvessel line.

The control part 10 executes the feature point extraction processing asthe above, and stores each partial blood vessel forming sequenceobtained as the processing result (feature points from the start pointvia a curve point to the finish point in a partial blood vessel line) inthe flash memory 13 (FIG. 1) as registration data D1 (FIG. 1).

Here, FIGS. 31A to 31C show the evaluation results by this feature pointextraction processing. These FIGS. 31A to 31C show three samples ofblood vessel lines before feature point extraction processing (whitepart in these figures), and blood vessel lines that were restored basedon the feature points extracted by the above feature point extractionprocessing (white part in these figures). As also obvious from theseFIGS. 31A to 31C, it is suggested that feature points were suitablyextracted by the feature point extraction processing. Further, whereasthe data of feature points in a blood vessel line before the featurepoint extraction processing was approximately 1 kBit, the data offeature points in the blood vessel line after the feature pointextraction processing was approximately 256 Bit.

As also obvious from this experiment result, the control part 10 cansuitably reduce information amount by the aforementioned feature pointextraction processing.

Note that, in the authentication, the control part 10 sequentiallyconnects segments from the start point sequentially via an adjacentcurve point to the finish point in a partial blood vessel formingsequence, for every partial blood vessel forming sequence, (featurepoints from the start point via a curve point to the finish point in apartial blood vessel line) of the registration data D1, and restores theblood vessel line.

(2-5) Conclusion

As the first feature point extraction processing as described above, inbranch points, end points, and curve points detected as the featurepoints of the outline, the control part 10 eliminates a curve point forevery group of feature points that were assigned as a group from abranch point or an end point to the next branch point or an end point(partial blood vessel forming sequence), by gradually switching from anelimination state of g rasping in perspective to an elimination state oflocally grasping so that the partial blood vessel line after eliminationbecomes simple (smooth), as well as approximating the forms of thepartial blood vessel line before elimination and the partial bloodvessel line after elimination (the elimination processing from thesecond stage to the fourth stage).

Thereby, the control part 10 can suitably reduce data amount, withoutlosing the meaning as identification information.

Furthermore, as preprocessing of the elimination processing (theelimination processing on the first stage), the control part 10eliminates a curve point existing in the neighborhood of a branch point.Thereby, the situation that is the elimination processing after thesecond stage, it is difficult to select other curve point that shouldbecome a feature component can be prevented, and a point as a featurecomponent of a blood vessel can be further suitably extracted.

Further, in end points, the control part 10 eliminates the end point inthat the distance to a curve point connected to it is short. At the sametime, in branch points on a blood vessel line, if there is a pair ofpartial blood vessel lines in that the intersection angle of three orthe four partial blood vessel lines extending from the branch points isclose to 180 degrees, the control part 10 sets a partial blood vesselforming sequence in the one pair of partial blood vessel lines as onepartial blood vessel forming sequence, and eliminates one of the startpoint and the finish point being the end points of the original partialblood vessel forming sequence.

Thereby, the control part 10 can eliminate a feature point withoutchanging the forms of the blood vessel lines before and afterelimination. Thus, data amount can be suitably reduced without losingthe meaning as identification information.

Further, as processing after the above feature point extractionprocessing, the control part 10 corrects the position of a feature pointso that a segment connecting a feature point that was remained after theabove feature point extraction processing passes through the most pixelsof the original blood vessel line. Thereby, the control part 10 can makethe meaning as identification information further effective.

On the other hand, as a technique for detecting a feature point in theoutline, the control part 10 sets an inputted imaged image as a binaryimage, and sets the outline width of blood vessels in the above binaryimage as one pixel. Then, the control part 10 detects an end point and abranch point from the blood vessel line of which the outline width isone pixel, and also detects a curve point, for every partial bloodvessel line from a branch point or an end point to the next branch pointor an end point, that is, in an unbranched segment unit.

Thereby, the control part 10 can remove a component surplus on detectinga point. Therefore, a feature point can be accurately detected withoutusing a complicated calculation technique. As a result, data amount canbe suitably reduced without losing the meaning as identificationinformation.

(3) Concrete Processing Contents of Feature Point Extraction ProcessingAccording to Second Embodiment

Next, concrete processing contents in second feature point extractionprocessing will be described. In function, as shown in FIG. 32 in thatthe same reference numeral is added to the corresponding part in FIG. 2,this second feature point extraction processing is formed by a featurepoint detecting part 21, a curve point eliminating part 122 and an endpoint eliminating part 123.

The second feature point extraction processing is different from thefirst feature point extraction processing in the point of adopting thecurve point eliminating part 122 that eliminates a curve point based onthe relationship between a segment connecting two feature points and anoriginal blood vessel line from one of the feature points to the otherfeature point, instead of the curve point eliminating part 22 (FIG. 2)that eliminates a curve point based on the relationship between afeature point being an elimination object and a feature point connectedto the feature point.

Furthermore, because the curve point eliminating part 122 corresponds toa part of the feature point correcting part 24 in the first featurepoint extraction processing, in the point of aiming at the relationshipbetween a segment connecting two feature points and an original bloodvessel line between these feature points. Therefore, the feature pointcorrecting part 24 is omitted from the second feature point extractionprocessing.

Further, the second feature point extraction processing is differentfrom the first feature point extraction processing, in the point ofadopting the end point eliminating part 123 only for executing the endpoint elimination processing on the above second stage, instead of theend point eliminating part 23 (FIG. 2) that executes the end pointelimination processing on the first stage and the second stage.

The above curve point eliminating part 122 and end point eliminatingpart 123 will be described in detail below.

(3-1) Elimination of Curve Point

The curve point eliminating part 122 eliminates a curve point as theoccasion demands, by setting feature points from the start point via acurve point to the finish point in a partial blood vessel line (that is,partial blood vessel forming sequence) that have been assigned as agroup by the feature point detecting part 21 as a processing unit.

Because the contents of the elimination processing of these partialblood vessel forming sequences are the same, the above contents will bedescribed by limiting to the case where a certain partial blood vesselforming sequence is used as a processing object, with reference to FIG.33, a square shows a pixel forming an original blood vessel line(hereinafter, this is referred to as an original blood vessel pixel),and a broken line is added to an end point and a curve point in theabove original blood vessel pixels.

In feature points from the start point via a curve point to the finishpoint in a partial blood vessel line, until the passing rate of asegment SG (SG₁-SG₃) connecting a base point GP_(bs) and a pointproposed for elimination GP_(cd) to original blood vessel pixels fromthe feature point selected as a base GP_(bs) (hereinafter, this isreferred to as a base point) to the point proposed for eliminationGP_(cd) (GP_(cd1)-GP_(cd3)) becomes smaller than a predeterminesthreshold value (hereinafter, this is referred to as a passing ratethreshold value), the curve point eliminating part 122 sequentiallyobtains the passing rate by sequentially shifting the above pointproposed for elimination GP_(cd) to the finish end side.

Referring to FIG. 33, the segment SG₁ passes through all of the originalblood vessel pixels (two pixels) from the base point GP_(bs) to acorresponding point proposed for elimination GP_(cd3). The segment SG₂passes through four pixels in the original blood vessel pixels (sevenpixels) from the base point GP_(bs) to the corresponding point proposedfor elimination of GP_(cd2). And the segment SG₃ passes through twopixels in the original blood vessel pixels (nine pixels) from the basepoint GP_(bs) to the corresponding point proposed for eliminationGP_(cd2). In this connection, practically, the passing ratio of asegment to an original blood vessel pixel means the rate of the numberof pixels overlapped to an original blood vessel pixel, to the number ofpixels of original blood vessel pixels from the base point GP_(bs) tothe point proposed for elimination GP_(cd), in the pixels forming asegment connecting the above base point GP_(bs) and the point proposedfor elimination GP_(cd).

If the passing rate of the segment SG₃ to the original blood vesselpixel is smaller than the passing rate threshold value, the curve pointeliminating part 122 eliminates a feature point GP_(cd1) between afeature point that was selected as a point proposed for eliminationGP_(cd2) preceding to the feature point that was selected as the pointproposed for elimination GP_(cd3) at the time, and the base pointGP_(bs). Thereby, the feature point GP_(cd1) can be eliminated, as wellas approximating the segment SG₂ from the remained feature pointGP_(cd2) to the base point GP_(bs) to the original blood vessel line.

Here, if the above passing rate threshold value is set to a small value,it may be caused that although the segment connecting the base point anda point proposed for elimination does not approximate to the originalblood vessel pixels from the above base point to the point proposed forelimination, the feature point GP_(cd) is reduced. On the contrary, ifthe passing rate threshold value is set to a large value, that it isdifficult to eliminate the feature point GP_(cd) may be caused.

Then, in this embodiment, the curve point eliminating part 122 switchesthe threshold value according to the segment length. Concretely, ifassuming that the base point GP_(J) (J=1, 2, . . . , M (M is aninteger)) and the ath point proposed for elimination from the base pointas GP_(j+a), in the case of obtaining the passing rate of the segmentGP_(J)-GP_(j+a) connecting the base point GP_(J) and the point proposedfor elimination GP_(j+a) to the original blood vessel pixel, when thesegment of which the passing rate was obtained immediately before that(hereinafter, this is referred to as an immediately-before segment)GP_(J+(a−1))-GP_(j+a) is above a predetermined threshold value(hereinafter, this is referred to as a segment threshold value), a firstpassing rate threshold value is set. On the contrary, when the segmentlength is less than the segment threshold value, a second passing ratethreshold value larger than the first passing rate threshold value isset.

Thereby, a curve point can be accurately selected, by that the partialblood vessel line after elimination can be smoothed, as well asapproximating the forms of the partial blood vessel line beforeelimination and the partial blood vessel line after elimination.

Concretely, this elimination processing of a curve point is executed ina procedure shown in flowcharts of FIGS. 34A-34D, from the start pointin a partial blood vessel forming sequence. That is, the curve pointeliminating part 122 selects the start point of the partial blood vesselforming sequence as a base point, and also selects the first featurepoint from the above base point as point proposed for elimination (stepSP31).

Then, the curve point eliminating part 122 determines whether to be thecase of obtaining a passing rate for the first time after started theelimination processing of a curve point, or whether theimmediately-before segment GP_(J+(a−1))-GP_(j+a) of the segmentGP_(J)-GP_(j+a) connecting the base point GP_(J) and a point proposedfor elimination GP_(j+a) that is a selection object at the present timeis less than the segment threshold value (step SP32).

If it is in the case of obtaining the passing rate for the first timeafter started the elimination processing a curve point, or in the casewhere the immediately-before segment GP_(J+(a−1))-GP_(j+a) is less thanthe segment threshold value, the curve point eliminating part 122 setsthe first passing rate threshold value as a passing rate threshold value(step SP33). And then the curve point eliminating part 122 obtains thepassing rate of the segment GP_(J)-GP_(j+a) connecting the base pointGP_(J) and the point proposed for elimination GP_(j+a) that is aselection object at the present time, to the original blood vessel pixel(step 34), and determines whether or not this passing rate is above thefirst passing rate threshold value (step SP35).

On the contrary, if the number of times to obtain the passing rate istwo times or more after started the elimination processing of a curvepoint, and if the immediately-before segment GP_(J+(a−1))-GP_(j+a) isabove the segment threshold value, the curve point eliminating part 122sets the second passing rate threshold value as a passing rate thresholdvalue (step SP36). And then, the curve point eliminating part 122obtains the passing rate of the segment GP_(J)-GP_(j+a) connecting thebase point GP_(J) and the point proposed for elimination GP_(j+a) thatis a selection object at the present time to the original blood vesselpixel (step SP34), and determines whether or not this passing rate isabove the second passing rate threshold value (step SP35).

Here, if the passing rate is above the passing rate threshold value,this means that the segment GP_(J)-GP_(j+a) connecting the base pointGP_(J) being a selection object at the present time and the approximatesto or the same as the original blood vessel line from the above basepoint GP_(J) to the point proposed for elimination GP_(j+a).

In this case, the curve point eliminating part 122 determines whether ornot the point proposed for elimination GP_(j+a) being a selection objectat the present time is the finish point of the partial blood vesselforming sequence (step SP37). When it is not the finish point, the curvepoint eliminating part 122 selects a feature point on the finish pointside to the feature point selected as the above point proposed forelimination GP_(j+a) (step SP38), and then the curve point eliminatingpart 122 returns to the aforementioned processing (step SP32).

On the contrary, if the passing rate is less than the passing ratethreshold value, this means that the segment GP_(J)-GP_(j+a) connectingthe base point GP_(J) being the selection object at the present time andthe point proposed for elimination GP_(j+a) is quite different from theoriginal blood vessel line from the above base point GP_(J) to the pointproposed for elimination GP_(j+a).

In this case, the curve point eliminating part 122 eliminates all of oneor more feature points between the feature point that has been selectedas the point proposed for elimination GP_(j+a) preceding to the presentpoint time and the feature point that is selected as the base pointGP_(j) at the present time (step SP39).

Then, the curve point eliminating part 122 determines whether or not thepoint proposed for elimination GP_(j+a) being the selection object atthe present time is the finish point of the partial blood vessel formingsequence (step SP40). If it is not the finish point, the curve pointeliminating part 122 selects the point proposed for elimination GP_(j+a)being the selection object at the present time as the base point GP_(j),and also selects the feature point on the finish point side to the basepoint GP_(j) as a new point proposed for elimination GP_(j+a) (stepSP41). And then, the curve point eliminating part 122 returns to theaforementioned processing (step SP32).

On the contrary, if the point proposed for elimination GP_(j+a) beingthe selection object at the present time is determined as the finishpoint of the partial blood vessel forming sequence (step (SP37 (Y) orstep SP40 (Y)), the curve point eliminating part 122 eliminates all orone or more feature points between the feature point selected as thepoint proposed for elimination GP_(j+a) at the present time and thefeature point selected as the base point GP_(j) at the present time(step SP42). And then, the curve point eliminating part 122 finishes theelimination processing of a curve point.

The curve point eliminating part 122 executes the elimination processingof a curve point by the above procedure. Note that, FIG. 35 shows thestate before the elimination processing and after the eliminationprocessing. FIG. 35 shows the case where the segment threshold value inthe elimination processing is set to 5 mm, the first passing ratethreshold value is set to 0.5 (50%), and the second passing ratethreshold value is set to 0.7 (70%). In FIG. 35, a square shows anoriginal blood vessel pixel, a circle shows a pixel forming a segment,and a broken line is added to an end point and a curve point in theoriginal blood vessel pixel.

As also obvious from this FIG. 35, it can be found that a curve pointcan be accurately remained, by that the partial blood vessel line afterelimination can be smoothed, as well as approximating the forms of thepartial blood vessel line before elimination and the partial bloodvessel line after elimination.

(3-2) Elimination of End Point

The processing is the same as the end point elimination processing onthe second stage in the end point eliminating part 23 (FIG. 2). Whenthere is a pair of partial blood vessel lines in that the intersectionangle of three or four partial blood vessel lines extending from abranch point in branch points on the blood vessel line is close to 180degrees, the end point eliminating part 123 assigns partial blood vesselforming sequences in the one pair of partial blood vessel lines as onepartial blood vessel forming sequence, and eliminates one of the startpoint and the finish point being the end points of the original partialblood vessel forming sequence.

Concretely, as described above with reference to FIGS. 24 and 25, in thebranch points on the blood vessel line, a partial blood vessel formingsequence in a pair of partial blood vessel lines satisfying thecondition that the cosine of the intersection angle of partial bloodvessel lines extending from the above branch point is smaller than asecond cosine threshold value is set as one partial blood vessel formingsequence, and one of the start point and the finish point being the endpoints of the original partial blood vessel forming sequence iseliminated.

The control part 10 executes the second feature point extractionprocessing as the above, and stores each partial blood vessel formingsequence obtained as the processing result (feature points from thestart point via a curve point to the finish point in a partial bloodvessel line) in the flash memory 13 (FIG. 1) as registration data D1(FIG. 1).

Here, FIGS. 36A to 36C show the evaluation results of this secondfeature point extraction processing. FIGS. 36A to 36C show three samplesof blood vessel lines before the second feature point extractionprocessing (white part in these figures), and blood vessel lines thatwere restored based on feature points extracted by the first featurepoint extraction processing or the second feature point extractionprocessing (white part in these figures).

As also obvious from these FIGS. 36A to 36C, it has been suggested thata feature point was suitably extracted by the feature point extractionprocessing. Further, whereas the data of a feature point in the bloodvessel line before the feature point extraction processing wasapproximately 1 kBit, the data of a feature point in the blood vesselline after the first feature point extraction processing and the secondfeature point extraction processing was approximately 256 Bit.

Further, time for the second feature point extraction processing wasshorter 1.48 times than the first feature point extraction processingfor 192 samples. This is because as processing for determining whetheror not be to be a desirable curve point as an elimination object,whereas the first feature point extraction processing eliminates a curvepoint via a plurality of stages so as to get to the detail after furtherbroadly grasping a partial blood vessel forming sequence, and thenproperly corrects the position of a remaining feature point so as toapproximate to an original blood vessel line, the second feature pointextraction processing eliminates a feature point other than the featurepoints forming a segment approximate to an original blood vessel line.The second feature point extraction processing does not eliminate afeature point via a plurality of stages, and the elimination stateincludes the processing corresponding to the correction in the firstfeature point extraction processing.

Note that, in comparison with the first feature point extractionprocessing, the second feature point extraction processing has somechange in the forms of blood vessel lines between before and afterelimination. However, it does not lose the meaning as identificationinformation, and there is no problem in the point of aiming at suitablyreducing data amount.

As also obvious from this experiment results, the control part 10 cansuitably reduce information amount by the aforementioned second featurepoint extraction processing, at higher speed than the first featurepoint extraction processing.

(3-3) Conclusion

As the second feature point extraction processing as the above, thecontrol part 10 sequentially obtains the passing rate of the segmentGP_(J)-GP_(j+a) connecting the base point GP_(J) and the point proposedfor elimination GP_(j+a) and the point proposed for elimination GP_(j+a)to the original blood vessel pixel, by sequentially shifting the abovepoint proposed for elimination GP_(j+a) to the finish point side, untilthe passing rate becomes smaller than the passing rate threshold value,for every feature point from a branch point or an end point to the nextbranch point or an end point that have been assigned as a group (partialblood vessel forming sequence) in the branch points, end points andcurve points detected as the feature points of the outline.

Then, when the passing rate became smaller than the passing ratethreshold value, the curve point eliminating part 122 eliminates all orone or more feature points between the feature point that was selectedas the point proposed for elimination GP_(j+a) preceding to the presenttime, and the feature point (start point) beginning selected as the basepoint GP_(j) at the present time. Further, the curve point eliminatingpart 122 selects the point proposed for elimination GP_(j+a) being theselection object at the present time as the base point GP_(j), being theselection object at the present time as the base point GP_(j), andsequentially shifts a feature point on the finish point side to the basepoint GP_(j) as the point proposed for elimination GP_(j+a), until thepassing rate becomes smaller than the passing rate threshold value.

That is, the curve point eliminating part 122 eliminates a feature pointthat is put between the both ends in a part of the outline including atleast more than three feature points were connected for every partialblood vessel forming sequence, the condition that the rate of a partoverlapped to the one part of the outline in the straight linesconnecting the above both ends to a part of the outline is above apredetermined threshold value, and the rate is the closest rate to theabove threshold value.

Thereby, in the control part 10, the processing contents are more simplethan the first feature point extraction processing (since a curve pointis eliminated not via a plurality of stages, and the elimination stateincludes the processing corresponding to the correction in the firstfeature point extraction processing). Therefore, the processing can beperformed at higher speed, and data mount can be reduced without losingthe meaning as identification information.

Further, the control part 10 switches the above passing rate thresholdvalue to the first passing rate threshold value, or the second passingrate threshold value larger than the first passing rate threshold value,according to the segment length of the immediately-before segmentGP_(J+(a−1))-GP_(j+a).

Thereby, the control part 10 can be accurately remain only curve point,by that can make the partial blood vessel line after elimination can besmoothed, as well as approximating the form of the partial blood vesselline before elimination to the partial blood vessel line afterelimination. Therefore, data amount can be further reduced withoutlosing the meaning as identification information.

(4) Other Embodiments

In the aforementioned embodiment, it has dealt with the case where ablood vessel is applied as an object included in the image of inputimage data. However, the present invention is not only limited to thisbut also a bioidentification object such as a fingerprint, mouthprintand a nerve may be applied, or a picture pattern such as a map and aphotograph may be applied. This means that the aforementioned processingby the control part 10 can be widely applied to various image processingsuch as used for preprocessing, interprocessing and postprocessing inother image processing, not only limited to image processing inbiometrics authentication.

Further, in the aforementioned embodiment, it has dealt with the casewhere curve point elimination processing or the like is executed aftersetting an inputted multivalue image to a binary image, and the outlinewidth of the outline to an object (blood vessels) included in the abovebinary image to one pixel. However, the present invention is not onlylimited to this but also curve point elimination processing or the likemay be executed on a binary image or a multivalue image including theobject outline having the outline width other than one pixel. Also inthis case, the same effect as the aforementioned embodiment can beobtained.

Note that, whether adopting either of the aforementioned first featurepoint extraction processing or second feature point extractionprocessing can be properly selected, according to the form of anembodiment applying this image processing and a type of an object or thelike. Further, the curve point elimination processing, end pointelimination processing and feature point correction processing in thefirst feature point extraction processing, or the curve pointelimination processing, and end point elimination processing the secondfeature point extraction processing can be properly selected, accordingto the form of an embodiment applying this image processing and a typeof an object or the like.

Further, in the aforementioned embodiment, as feature point detectionprocessing, it has dealt with the case where the processing havingcontent described as to the feature point detecting part 21 is applied.However, the present invention is not only limited to this but alsofeature point detection processing called the Harris corner, andalready-known feature point detection processing may be applied insteadof this. Also in this case, as to a part of the aforementionedembodiment, the same effect can be obtained.

Further, in the aforementioned embodiment, it has dealt with the casewhere the feature point of a blood vessel line represented in the seconddimension (xy coordinate system) (hereinafter, this is referred to as atwo-dimensional blood vessel line) is extracted by the first featurepoint extraction processing or the second feature point extractionprocessing. However, the present invention is not only limited to thisbut also it is also possible to extract a blood vessel line representedin the three dimensions (xyz coordinate system) such as a voxel(hereinafter, this is referred to as a three-dimensional blood vesselline) by the first feature point extraction processing or the secondfeature point extraction processing.

However, because a three-dimensional blood vessel line is a solid image,it is necessary to change the setting of a search area to detect an endpoint, a branch point and a curve point in the above three-dimensionalblood vessel line.

That is, in both of the case of detecting an end point and a branchpoint (FIGS. 4A to 4C) and the case of detecting a curve point in theabove blood vessel line (FIGS. 6 and 9A-9C), a search area for atwo-dimensional blood vessel line has been set as the surrounding eightpixels in the xy direction centering an aimed pixel (hereinafter, thisis referred to as two-dimensional surroundings). On the other hand, asshown in FIG. 37, a search area SAR for a three-dimensional blood vesselline is set as the surrounding 26 pixels in the xyz direction centeringan aimed pixel ATP (hereinafter, this is referred to asthree-dimensional surroundings).

In this connection, in the case of detecting a feature point in athree-dimensional blood vessel line, similarly to the feature pointdetecting part 21 for detecting a feature point in a two-dimensionalblood vessel line, on a first stage, for example, as shown in FIGS. 38Ato 38C, when one pixel exists in the search area SAR centering the aimedpixel ATP (FIG. 38A), the aimed pixel ATP is detected as an end point.On the other hand, when three pixels exist in the search area SAR (FIG.38B) or when four pixels exist (not shown), the aimed pixel ATP isdetected as a branch point. And when a pixel does not exist in thesearch area SAR (FIG. 38C), the aimed pixel ATP is detected as anisolated point.

Further, on a second stage, by setting the end point and branch pointdetected on the first stage as the start point or the finish point, acurve point in the blood vessel line from the above start point to endpoint (partial blood vessel line) is detected. Concretely, for example,as shown in FIG. 39, in blood vessel pixels existing in thethree-dimensional surrounds (the search area SAR) of the present aimedpixel (a pixel represented by net hatching), a blood vessel pixel (apixel represented by check hatching) except the blood vessel pixel thatwas set as the aimed pixel before (a pixel represented by horizontalhatching) is set as the next aimed pixel. And continuous aimed pixelsare sequentially tracked from the start point, until a blood vesselpixel existing in the three-dimensional surroundings (the search areaSAR) of the above present aimed pixel becomes the finish point. In thistracking process, when the linearity of the aimed pixel that is set asthe next aimed pixel, the above present aimed pixel is detected as acurve point.

In this manner, by setting a search area SAR as the surrounding 26pixels in the XYZ direction centering the aimed pixel ATP (hereinafter,this is referred to as three-dimensional surroundings), athree-dimensional blood vessel line can be extracted by the firstfeature point extraction processing or the second feature pointextraction processing.

Note that, in the case of detecting a curve point in a two-dimensionalblood vessel line, it is considered that a point on a straight line andan appearing pattern in the neighborhood of a curve point becomesignificant, and a tracking order pattern for the pixels in theneighborhood of the aimed pixel is set according to the positionalrelationship between the present aimed pixel and the immediately-beforeaimed pixel.

Also in the case of detecting a curve point in a three-dimensional bloodvessel line, a point on a straight line and an appearing pattern in theneighborhood of a curve point become significant. Therefore, thetracking order pattern is set according to the positional relationshipbetween the present aimed pixel and the immediately-before aimed pixel.However, since a blood vessel line is a solid image, in the positionalrelationship between the present aimed pixel and the immediately-beforeaimed pixel, z direction is added in addition to xy direction (FIGS. 9Ato 9C), and the number of the tracking order patterns increases. Thus,it is necessary to pay attention.

The description of concrete tracking order patterns will be omittedbecause the number is large. However, in the case where a z component inthe position vector of the present aimed pixel to the immediately-beforeaimed pixel is other than “0”, that is, in the case where there is aposition change in the z direction between the immediately-before aimedpixel and the present aimed pixel, as shown in FIG. 40A, as a searcharea SAR, areas equally divided into three in the direction orthogonalto z axis SAR₁, SAR₂, SAR₃ are set as one group.

On the contrary, in the case where there is not a position change in thez direction between the immediately-before aimed pixel and the presentaimed pixel, as shown in FIG. 40B, as the search area SAR, the trackingorder pattern is set by setting areas equally divided into three in thedirection parallel to the z axis SAR₄, SAR₅, SAR₆ as one group.

Because the data amount of these tracking order patterns becomecomparatively large, instead of storing the above tracking orderpatterns, in the case where there is a position change in the zdirection between the immediately-before aimed pixel and the presentaimed pixel, in the area that the search area SAR is equally dividedinto three in the direction orthogonal to the Z axis, the area SAR₁ orSAR₃ except an area including the immediately-before aimed pixel and thepresent aimed pixel is set as a first search area. In the case wherethere is not position change, in the area that the search area SAR isequally divided into three in parallel to the Z axis, a search may beperformed by setting the area SAR₅ including the present aimed pixel asa first search area.

In this manner, by switching a pattern to divide a search area SARaccording to the presence of a position change in the z directionbetween the immediately-before aimed pixel and the present aimed pixel,and determining an area to be first search according to the positionrelationship between the immediately-before aimed pixel and the presentaimed pixel in each area SAR₁, SAR₂, SAR₃, SAR₄, SAR₅, SAR₆ divided bythe above switched pattern, a curve point can be detected at higherspeed while reducing the data amount of tracking order patterns, incomparison with the case of uniformly tracking all pixels in thethree-dimensional surroundings of the above present aimed pixel.

The present invention is applicable to the field of image processing,more particularly to the case of extracting points forming a line in animage.

While there has been described in connection with the preferredembodiments of the present invention, it will be obvious to thoseskilled in the art that various changes, modification, combinations,sub-combinations and alternations may be aimed, therefore, to cover inthe appended claims all such changes and modifications as fall withinthe scope of the present invention.

1. A computer-implemented image processing method, executed by aprocessor, for eliminating a feature point being a feature as acomponent of an outline, in the outline of an object included in theimage of inputted image data, the method comprising: a first step ofassigning feature points including at least one of a first branch point,a first end point, a second branch point, and a second end point, frombranch points, end points and curve points detected as said featurepoints of said outline; and a second step of eliminating a middlefeature point of three continuous feature points, the three continuousfeature points including a first feature point, a second feature point,and the middle feature point located between the first and the secondfeature points, where the middle feature point is eliminated when theproduct of the vector formed by the first feature point and the middlefeature point and the vector formed by the middle feature point and thesecond feature point is smaller than a predetermined threshold value. 2.The image processing method according to claim 1, wherein: the secondincludes further includes a preprocessing step of eliminating a featurepoint existing in the neighborhood of said detected branch point, beforeeliminating the middle feature point of said three continuous featurepoints.
 3. The image processing method according to claim 1, wherein:the second step further includes eliminating a middle feature point whena cosine of the angle between the vector formed by the first featurepoint and the middle feature point and the vector formed by the middlefeature point and the second feature point if smaller than apredetermined cosine threshold value.
 4. The image processing methodaccording to claim 1, including: a step of replacing two continuousfeature points when a segment connecting the continuous two featurepoints is smaller than a predetermined segment threshold value, whereinthe two continuous feature points are replaced by an inner dividingpoint located on a line connecting the two continuous feature points. 5.The image processing method according to claim 1, including: a step ofreplacing two continuous feature points when: a segment connecting thecontinuous two feature points is smaller than a predetermined segmentthreshold value, and signs of positive and negative are the same for theproduct of: a line connecting an adjacent feature point and a firstfeature point of the two continuous feature points, and an other lineconnecting an other adjacent feature point and a second feature point ofthe two continuous feature points; wherein the two continuous featurepoints are replaced by an inner dividing point located on a lineconnecting the two continuous feature points.
 6. The image processingmethod according to claim 1, including: the second step further includeseliminating the middle feature point when the absolute value of theproduct is smaller than a predetermined product threshold value.
 7. Theimage processing method according to claim 1, including: a step ofeliminating at least one of the first and second end points when thedistance to a feature point connected to at least one of the first andsecond end points is smaller than a predetermined distance thresholdvalue.
 8. The image processing method according to claim 1, including: astep of assigning, after said middle feature point is eliminated, afirst and a second outline segments connecting the at least two of thefirst branch point, the second branch point, the first end point, andthe second end point, wherein the cosine of the intersection angle ofthe first and second outline segments is smaller than a predeterminedsecond cosine threshold value.
 9. The image processing method accordingto claim 1, including: a step of sequentially selecting, after saidmiddle feature point is eliminated, a remaining feature point as aposition change object, from two feature points forming the longestoutline segment; and a step of changing the feature point selected assaid position change object to a position corresponding to a straightline that passes through the most pixels forming said outline.
 10. Theimage processing method according to claim 1, including: a step ofreplacing two continuous feature points when a segment connecting thecontinuous two feature points is smaller than a predetermined segmentthreshold value, wherein the two continuous feature points are replacedby point located at the intersection of a line that extends from anadjacent feature point through a first feature point of the twocontinuous feature points and, and an other line that extends from another adjacent feature point through a second feature point of the twocontinuous feature points.
 11. The image processing method according toclaim 1, including: a step of replacing two continuous feature pointswhen: a segment connecting the continuous two feature points is smallerthan a predetermined segment threshold value, and signs of positive andnegative are different for the product of: a line connecting an adjacentfeature point and a first feature point of the two continuous featurepoints, and an other line connecting an other adjacent feature point anda second feature point of the two continuous feature points; wherein thetwo continuous feature points are replaced by point located at theintersection of a prolongation line that extends from the adjacentfeature point through the first feature point and, and the otherprolongation line that extends from the other adjacent feature pointthrough the second feature point.
 12. An image processing apparatus foreliminating a feature point being a component of an outline, in theoutline of an object included in the image of inputted image data,comprising: a feature point detecting unit configured to assign featurepoints including at least one of a first branch point, a first endpoint, a second branch point, and a second end point, from the branchpoints, end points and curve points detected as said feature points ofsaid outline; and a curve point eliminating part configured to eliminatethe middle feature point of three continuous feature points, the threecontinuous feature points including a first feature point, a secondfeature point, and the middle feature pint located between the first andthe second feature point; wherein the middle feature point is eliminatedwhen the product of the vector formed by the first feature point and themiddle feature point and the vector formed by the middle feature pointand the second feature point is smaller than a predetermined thresholdvalue.
 13. A non-transitory computer-readable storage medium comprisinga program which, when executed by a computer, performs a method formaking image processing means for eliminating a feature point being acomponent of an outline, in the outline of an object included in theimage of image data stored in storing means, the method inducing:assigning the feature points including at least one of a first branchpoint, a first end point, a second branch point, and a second end point,from the branch points, end points and curve points detected as saidfeature points of said outline; and eliminating a middle feature pointof three continuous feature points, the three continuous feature pointsincluding a first feature point, a second feature point, and the middlefeature point located between the first and the second feature points,where the middle feature point is eliminated when the product of thevector formed by the first feature point and the middle feature pointand the vector formed by the middle feature point and the second featurepoint is smaller than a predetermined threshold value.
 14. Acomputer-implemented image processing method, executed by a processor,for eliminating a feature point being a feature as a component of anoutline, in the outline of an object included in the image of inputtedimage data, the method comprising: assigning the feature pointsincluding at least one of a first branch point, a second end point, asecond next branch point, and a second end point, from branch points,end points and curve points detected as said feature points of saidoutline; eliminating a middle feature point of a set of continuousfeature points, the continuous feature points including a first featurepoint, a second feature point, and the middle feature point locatedbetween the first and second feature point, where the middle featurepoint is eliminated when the product of the vector formed by the firstfeature point and the middle feature point and the vector formed by themiddle feature point and the second feature point is smaller than apredetermined threshold value; and extracting at least one feature pointother than the middle feature point, when two or more feature points areconnected and the connected line corresponds to said outline.